SDI Convergence - Global Spatial Data Infrastructure Association

Some differences are not clear from the models, but were identified by comparing the
datasets. Therefore our first recommendation, before harmonising the models, is to
model any information about the content and meaning of datasets that is currently not
included in the domain models, e.g. acquisition rules. This allows harmonising and integrating
this information as well. For example, the current TOP10NL acquisition rules
state that railway banks are not measured, despite the presence of the class Railway in
the model.
Many differences between the information models are caused by difference in perspective
(section 2.1). These different perspectives cannot easily be harmonised because
they are justified by differences in objectives, source data, application domain, providers,
and acquisition methods. However, the law on key registers provides potentials for
harmonising some parts of the perspective. Specifically two aspects of the law enforce
municipalities to inform the Kadaster about updates for TOP10NL data. The first aspect
is that any user of the key register must inform the provider when (s)he notices an error.
Secondly, municipalities are obliged to use the Kadaster’s TOP10NL data, updated
every 2 years, instead of their self-produced 1:10k datasets, updated more frequently.
To effectuate updates in TOP10NL data as soon as possible, some large municipalities
will send TOP10NL updates based on their 1:10k datasets. For this purpose they are
currently converting their 1:10k datasets into TOP10NL compliant datasets. This practice
makes the integration issue of the two topographic datasets, i.e. IMGeo and
TOP10NL, relevant within municipalities.
Because not all information on the data is laid down in the TOP10NL model, TOP10NL
data can be generated from a municipal perspective without violating the model. An
example is that the Kadaster often assigns road areas that are too small to be area objects
(smaller than 2 meters) to terrain. However, assigning these areas to neighbouring
roads better supports the municipal maintenance task of public area and fits better
with the definition of PartOfRoad in the TOP10NL model. Consequently municipal
TOP10NL roads may cover the full construction of all IMGeo road objects which solves
the differences in object demarcation of roads (section 2.3). To illustrate this, two
TOP10NL road implementations, one generated by Kadaster and one generated by
municipality of Rotterdam, are compared with IMGeo roads in Figure 3.
Obviously this poses new research questions, since now the differences in perspective
do not occur between IMGeo and TOP10NL, but within one dataset, i.e. TOP10NL. In
conclusion, to solve the differences in object demarcation it is most important to make
these demarcations unambiguously explicit in the models. In a next step it can be studied
whether differences can be aligned and how.
A first step in harmonising differences in main classes (section 2.2) is to model more
specialisations (i.e. subclasses). The result will be more homogenous classes on which
it is easier to agree. Figure 4 shows an example. The left part of the figure shows the
current Terrain class in TOP10NL with its different attribute values for different types of
terrain. Integrating IMGeo and TOP10NL requires agreeing on the concept of Terrain.
The alternative modelling with subclasses for different types of terrain (Figure 4, right)
requires only agreeing on the definition of types of terrain, for example, Farmland or
Forest.
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